Hybridization of Machine Learning Algorithms and an Empirical Regression Model for Predicting Debris-Flow-Endangered Areas

Landslide Classification and Prediction of Debris Flow Using Machine Learning Models

(2023) A. Shameem Ansar et al.   IETE JOURNAL OF RESEARCH

Comparison of Machine Learning and Traditional Statistical Methods in Debris Flow Susceptibility Assessment: A Case Study of Changping District, Beijing

(2023) Feifan Gu et al.   Water

Editorial for Advances and applications of deep learning and soft computing in geotechnical underground engineering

(2022) Wengang Zhang et al.   Journal of Rock Mechanics and Geotechnical Engineering

A data-driven method for predicting debris-flow runout zones by integrating multivariate adaptive regression splines and Akaike information criterion

(2022) Mi Tian et al.   Bulletin of Engineering Geology and the Environment

Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge

(2022) Wengang Zhang et al.   GONDWANA RESEARCH

Artificial Neural Network-based prediction of glacial debris flows in the ParlungZangbo Basin, southeastern Tibetan Plateau, China

(2020) Wang Tang et al.   Journal of Mountain Science

An artificial neural network model to predict debris-flow volumes caused by extreme rainfall in the central region of South Korea

(2020) Deuk-Hwan Lee et al.   ENGINEERING GEOLOGY

Land-Cover Classification of Coastal Wetlands Using the RF Algorithm for Worldview-2 and Landsat 8 Images

(2019) Xiaoxue Wang et al.   Remote Sensing

Empirical relationships for the estimation of debris flow runout distances on depositional fans in the Wenchuan earthquake zone

(2019) Wei Zhou et al.   JOURNAL OF HYDROLOGY

Geometrical Characterization of Sediment Deposits at the Confluence of Mountain Streams

(2018) et al.   Water

A Multivariate Adaptive Regression Splines model for determining horizontal wall deflection envelope for braced excavations in clays

(2018) Wengang Zhang et al.   TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY

Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach

(2016) A. T. C. Goh et al.   Bulletin of Engineering Geology and the Environment

Changes in runout distances of debris flows over time in the Wenchuan earthquake zone

(2013) Shuai Zhang et al.   Journal of Mountain Science

The perfect debris flow? Aggregated results from 28 large-scale experiments

(2010) Richard M. Iverson et al.   JOURNAL OF GEOPHYSICAL RESEARCH

An empirical–statistical model for predicting debris-flow runout zones in the Wenchuan earthquake area

(2010) Chuan Tang et al.   QUATERNARY INTERNATIONAL

Field and laboratory investigations of runout distances of debris flows in the Dolomites (Eastern Italian Alps)

(2009) Vincenzo D'Agostino et al.   GEOMORPHOLOGY

Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation

(2009) J.D. Rodriguez et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Debris-flow runout predictions based on the average channel slope (ACS)

(2008) Adam B. Prochaska et al.   ENGINEERING GEOLOGY

Evaluation of approaches to calculate debris-flow parameters for hazard assessment

(2008) Marcel Hürlimann et al.   ENGINEERING GEOLOGY